Online Dating Profile Rating and Message Blurring Mechanism
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Online dating systems lack user community-driven profile rating methods, leading to ineffective matching and user dissatisfaction, as they either limit matches in free-to-use systems or require excessive payment in subscription-based systems, without guaranteeing successful interactions.
Innovation Solution
A method and apparatus that store user profiles and increment/decrement ratings based on message interactions, allowing users to rate each other's profiles dynamically, with pay-per-match fees only when both parties engage, and automatic message deletion if not opened within a timeframe, to enhance user experience and reduce spamming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If free-to-use systems limit the number of matches, then system cost is reduced, but user satisfaction deteriorates
Solution Approach 1:
The system dynamically changes the parameter of match availability based on user profile ratings. High-rated users receive increased match quotas and access to premium features, while low-rated users receive limited matches. This resolves the contradiction by making system resources (matches) adaptive to user quality, reducing waste on low-engagement users while satisfying high-value users without requiring uniform subscription fees from all users.
2Adaptability or versatility
If subscription-based systems do not guarantee a match, then system flexibility is maintained, but reliability deteriorates
Solution Approach 1:
The system performs preliminary actions by calculating and storing user profile ratings before the matching process. These pre-computed ratings serve as reliability indicators that predict match success probability. When users subscribe, the system guarantees matches based on these pre-established rating thresholds, maintaining flexibility in pricing while providing reliability through data-driven match probability assessments.
3Manufacturing precision
If user community-driven profile rating methods are implemented, then matching quality is improved, but device complexity increases
Solution Approach 1:
The system implements self-service by enabling users to automatically rate each other's profiles based on interaction behavior (message opening, response time, engagement level). The rating algorithm autonomously processes interaction data and updates profile scores without manual intervention. This resolves the contradiction by automating the complex rating computation, improving matching quality through community feedback while keeping the user interface simple and the backend complexity hidden.
4Object-generated harmful factors
If message blurring and opening confirmation are implemented, then spamming is reduced, but ease of operation deteriorates
Solution Approach 1:
The system introduces an intermediary mechanism (blurred message preview with opening confirmation) between the sender and receiver. The blur acts as a gatekeeper that filters out low-quality spam messages by requiring explicit user consent to view full content. This resolves the contradiction by providing a simple yes/no interaction for users while automatically blocking spam, thus reducing harmful messages without significantly complicating the user experience for legitimate communications.
Data Source
AI summary
Embodiments herein provide a method for managing interactions between online users by an apparatus. A first user is associated with a first electronic device, a first user profile and a first user profile rating. A second user is associated with a second electronic device, a second user profile and a second user profile rating. The method includes sending from the first user to the second user, a first message and a link to view the first user profile. The method includes displaying on the second electronic device a blurred version of the first message content and a user interface eliciting an input to open or not open the message. The method includes determining whether the second user opens the first message or not. In an embodiment, the method includes incrementing the first and second user profile ratings, in response to determining that the second user opens the first message.